Abstract
Background: Robotic and gravity-balancing exoskeletons, originally designed for the rehabilitation training of neurological patients, are now being increasingly applied in objective and fine-grained sensor-based assessments of upper limb function. However, gravity compensation, inertia and damping properties of the exoskeleton interfere with the natural sensorimotor interaction, proprioceptive and visual feedback during movement execution. This may endanger the validity of the kinematic assessments in relation to the clinical outcome measures that they were supposed to reflect. Here, we appliedMethods: In a proof of concept study involving nineteen severely impaired chronic stroke patients, we assessed sensor-based kinematic data acquired with a multi-joint arm exoskeleton and compared it to the clinical outcome measure Upper Extremity Fugl-Meyer Assessment (UE-FMA) scale. During this assessment, real-time movement feedback of the system’s seven degrees of freedom was provided with a biomorphic 3D virtual representation of the upper limb, including the proximal component of the arm. To align posture and to minimize the exoskeleton-patient interaction, the same position (neutral zero) with a distance of 90 degrees between forearm and upper arm was taken as the starting position for all assessments. Within self-contained tasks, we assessed separately and subsequently the range of motion/spatial posture of four single joints (i.e., joint angles of wrist, elbow, arm, and shoulder movement) and the closing and opening of the hand with a pressure sensor placed in the handle.Results: A strong correlation was observed between wrist and elbow movements within the kinematic parameters (r > 0.7, p<0.003; Bonferroni corrected). A multiple regression model predicted the UE-FMA significantly (F (5, 13) = 12.22, p < 0.0005, adj. R2 = 0.83). Both shoulder rotation and grip pressure added significantly (p < 0.05) to the prediction with the standardized coefficients β of 0.55 and 0.38, respectively.Conclusions: Exoskeleton-based evaluation of single-joint movements and grip force facilitates the assessment of upper limb kinematics after stroke with high structural and convergent validity. Proximal and distal measures may contribute independently to the prediction of the clinical status.
Upper Limb Rehabilitation System for Self-Supervised Therapy: Computer-Aided Daily Performance Evaluation for the Trauma and Disorder in the Spinal Cord and Peripheral Nerves
